AI Powered Unmanned Aerial Vehicle for Payload Transport Application

Reem Alshanbari, Sherjeel M. Khan, Nazek Elatab, Muhammad Mustafa Hussain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Recently unmanned aerial vehicles (UAV) have received a growing attention due to their wide range of applications. Here, we demonstrate UAVs with artificial intelligence (AI) capabilities for application in autonomous payload transport. An algorithm is developed for target detection with multiple phases on the ground, which once the target is detected, would trigger the release of the payload that is attached on the drone. The experimental results show that the average frame rate over x seconds achieved a 19.4010717352 fps (frame per second) detection speed. Releasing the payload is achieved using a 3D printed system based on rack and pinion gears. In addition, auto flight program is developed to enable the autonomous movement of the drone. As a proof-of-concept, a small drone known as "Phantom DJI" is used for.6 kg autonomous payload transport along a predefined route to a target location.
Original languageEnglish (US)
Title of host publication2019 IEEE National Aerospace and Electronics Conference (NAECON)
PublisherIEEE
Pages420-424
Number of pages5
ISBN (Print)9781728114163
DOIs
StatePublished - Apr 10 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2015-Sensors-2707, OSR-2016-KKI-2880
Acknowledgements: The work is supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. Sensor Innovation Initiative OSR-2015-Sensors-2707 and KAUST-KFUPM Special Initiative OSR-2016-KKI-2880

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